docs: def extract(self, text: str, get_attr=['PERSON', 'ORG', 'GPE']) -> List[Extraction]:
          """
          Args:
              text (str): the text to extract from.
              get_attr (List[str]): The spaCy NER attributes we're interested in.
  
          Returns:
              List(Extraction): the list of extraction or the empty list if there are no matches.
          """
          doc = self.__nlp(text)
          attr_list = list()
          for ent in doc.ents:
              if ent.label_ in get_attr:
                  attr_list.append(Extraction(extractor_name=self.name,
                                              start_char=int(ent.start_char),
                                              end_char=int(ent.end_char),
                                              value=ent.text,
                                              tag=ent.label_,
                                              start_token=ent.start,
                                              end_token=ent.end))
          return attr_list